Last week, I issued a challenge. If you’re the type to call a pitcher who sports an inflated HR/FB rate “homer-prone”, I asked you to prove that this was not merely bad luck, but skill-related (or a lack of skill). I have been writing about fantasy baseball for 7+ years now and nothing bothers me more than when a definitive claim is made with no supporting evidence. There is a difference between “Pitcher X is homer-prone” and “Pitcher X has been homer-prone”. The former suggests an inherent lack of skill in keeping fly balls in the park, while the latter makes no such commentary on the pitcher’s home run avoidance skills, but merely describes what has happened.
Since it’s clear that we really don’t know for sure what leads to home run suppression skills or a lack thereof, at this point, only the aforementioned latter description seems appropriate in my mind. So Brandon McCarthy’s early struggles with gopheritis, which has carried over from last year’s issues, was what motivated me to challenge you, as I figured the homer-prone label would start popping up everywhere.
As I had hoped, my challenge sparked some great discussion. So today I’ll highlight some of the more interesting comments. Even if we can’t come up with definitive answers now, we will be better prepared for what to look for and research once better data is available.
Several commenters asked about the distance of a pitcher’s fly balls allowed. I analyze the hitter side and even developed an equation to predict HR/FB rate. I had completely forgotten that I actually researched a pitcher’s average fly ball distance and posted about it back in January!
I first calculated the year-over-year correlation of a pitcher’s batted ball distance. It came out to .308, which is worse than for hitters, but still meaningful. Then I took things a step further, calculating the correlation between distance and HR/FB rate, which sat at .442. Again, significantly worse than for hitters, but still something. Last, I tried to devise an xHR/FB rate for pitchers like I did for hitters, using the same three components. Unfortunately, the R-squared was just .276.
Anyway, now we know that a pitcher’s batted ball distance again does convey something, but less something than for hitters. Let’s check out McCarthy’s distance trend (through his second start):
So McCarthy’s HR/FB rate has pretty much trended along with his batted ball distance allowed. This doesn’t tell us anything of course. We’re trying to figure out whether that batted ball distance allowed is a fluke/bad luck and if not, why is it suddenly so inflated?
Now let’s get to some comments.
I also looked at heatmaps under the hypothesis that HR/FB% could be related to the percentage of pitches thrown in the middle of the strike zone, but noticed something else instead. What I saw, and what is presumably related to the above point regarding fly-ball percentages, is that pitchers who throw a high percentage of pitches in the bottom third of the strike zone have high HR/FB percentages whereas pitchers who throw a high percentage of pitches in the upper third of the strike zone have low HR/FB percentages.
When Brandon McCarthy threw up in the zone more than most, he had a HR/FB% better than most. When he changed to throwing down in the zone more than most, he had a HR/FB% worse than most.
Only a handful of examples were provided and no full study performed due to how time-consuming collecting the data is. But it’s interesting to note and certainly intriguing enough to look into further. There have been conflicting studies on whether ground ball pitchers allow higher or lower HR/FB rates and selection/survivor bias plays a role.
Because he’s a sinkballer.
Pitchers who feature the sinker as their primary pitch typically have a high HR/FB%. Look at Edison Volquez for example—in 2014 his sinker had an HR/FB of 17.2%. Not very unlike McCarthy’s, which was 17.7% in 2014. Masterson was 15.2% in 2013 but inflated to 25% in 2014 due to a massive reduction in the velocity of his sinker.
Sinkballers let up more homeruns.
It is absolutely, statistically true that pitchers who feature the sinker as their primary pitch have a higher HR/FB% when compared to all other pitchers.
Again, only a couple of cherry picked examples, but this seems to relate to jdbolick’s comment above. You would assume the sinker guys would be the same as those pitching more to the bottom of the zone. Although Rowen claims it is “statistically true”, no actual evidence was provided. This was the entire point of my challenge! He may very well be right, but I need to see some data that supports such a conclusion.
Eno Sarris says:
I found no correlation between zone% or sinker usage and HR/FB.
I found a tiny correlation between o-swing and HR/fB R-Squared: 0.0524017.
Finally, some facts! What Eno found looks to have eliminated the sinker usage theory that Rowen was so confident was true.
But then Rowen was back, this time with a chart. No description of exactly what his study involved, and whether it was the pitcher’s career HR/FB rate and sinker usage or what. And it was only a handful of pitchers. But it certainly seems like a positive trend:
This chart seems to disagree with what Eno found, so I’m curious what each looked at.
I also received an email from Zachary Smith, who I quickly learned develops his own projections and is a true data ninja. Perfect!
He told me:
I’ve actually done a few thousand hours of research on this topic and many others as I do my own projections system yearly. It turns out a pitcher does have some control over their HR/FB rate, but it’s not directly related to the “quality of their stuff”.
HR/FB rate is related to two factors: first, one’s FB%; secondly, one’s true infield fly ball percentage. We all know that IFFB% is actually not the percentage of infield fly balls; rather, it is the percentage of fly balls that are infield fly balls. By true IFFB% I mean one simply goes one step further and multiplies FB% and IFFB% to arrive at the number of balls in play that are infield fly balls.
It turns out one’s HR/FB rate = – 0.155*TrueIFFB% – 0.0585*FB% + 0.12
…the one aspect of batted ball distribution that a pitcher does control is what I call the “wedge”.
The “wedge” I refer to is the trajectory of the ball off the bat as viewed from the side. It turns out that a pitcher can tilt this wedge upwards or downwards and also widen the range of probable distributions or more tightly control that distribution. I’m still researching how this happens, but it is a repeatable yearly skill that is revealed in one’s FB% and IFFB% which, at the moment, is what we care about.
What one is trying to limit is hard hit fly balls. When one tilts the wedge upwards the hard hit fly balls move into a slot of lower probability on this wedge. This stacks up with evidence that has been accrued in the past showing that fly ball pitchers have slightly lower HR/FB rates. Further, pitchers who generate a lot of infield fly balls show that they have either tilted the wedge much higher or have widened the outcome of distributions, both factors that positively affect HR/FB.
P.S. McCarthy, while sporting a league average 38% fly ball percentage so far this year has sported below average fly ball rates (mid twenties) the last two years and below average infield fly ball rates (league average is about 9.6%) of 8.7% and 6.5% yielding well below average true IFFB% rates of 2.4% and 1.6% respectively. McCarthy deserves some of his inflated HR/FB% but, as you’ll notice, the most extreme HR/FB rate possible according to my regression line is 12% and that’s if you throw 99.999% ground balls and generate no pop ups. McCarthy may have earned some of his poor luck, but certainly not the lion’s share of it.
So what Zachary has found in his deep research is that fly ball pitchers who induce lots of pop-ups have slightly lower HR/FB rates. I could swear I read one study that concluded the opposite, though the others all agreed with what Zachary found. Still, McCarthy’s batted ball distribution certainly doesn’t justify a HR/FB rate so significantly above the league average.
So while it is seemingly far too time-consuming and difficult to do the research with the data currently available, we have some avenues to go down. We should look at pitch mix and location, velocity I guess, and batted ball distribution. Eventually, we should know a lot more about which kind of pitchers could suppress homers per fly ball and who might suffer from an inflated mark.
Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.